O.6.1-2 Motor competencies of elementary-school aged children – investigating the conjoint impact of parenting, school grounds quality, children’s movement behavior and self-confidence
Bibliographic record
Abstract
Abstract Purpose To understand factors that impact on children’s motor competencies (MCs) from a socio-ecological perspective. Methods The study is a cross-sectional sub-study of a three-year longitudinal cohort study called ‘Physical Literacy for communities (PL4C)’ in the West Vancouver school district. Motor competencies were assessed by the Physical Literacy Assessment for Youth (PLAY) Fun tool. Children were asked to perform 18 different movement tasks across five domains: running, locomotor, upper and lower body control, balance. Children’s objective physical activity was measured using wrist-worn accelerometer Actigraph GT3X+BT. Through a survey, parents were asked about their children’s amount of time playing outside during workdays and weekdays as well as time doing sports or instructor-led physical activity. The Activity Support Scale for Multiple Groups (ACTS-MG) were included in the survey measuring parental support for children’s physical activity. Quality of the 14 school grounds was measured by using the Sport, Physical activity and Eating behavior: Environmental Determinants in young people (SPEEDY) school grounds audit tool existing of six component scores: cycling provision, walking provision, sports and play facilities provision, other facility provision, design of the school grounds, aesthetics. Results Complete assessment of motor competencies (with PlayFun) were done for 319 children with average age of 7.5 years (90%; 166 boys, 147 girls, 6 non-binaries), whereof the majority was on an emerging- level (79%) regarding overall MC and one fifth on competent- level (n = 67). Participants accumulated MVPA about 111 minutes per day (113 min/d for boys, 109 min/d for girls, p = 0.37). Children with competent-level MC had in average 15 minutes/day more MVPA compared to children with emerging-level MC (p = 0.001). Analysis with structural equation modeling (SEM) revealed that direct significant effects of parenting, school grounds quality, children’s movement behavior varied for each MC and overall MC and between gender. ‘Logistics’ turned out to influence significantly positive most often, and had a positive significant effect on males and females overall MC (g = 0.267, p = 0.004 and g = 0.247, p = 0.011). Conclusions Beside parents logistics support and participation in sports, school grounds seems to impact positively children’s MCs, yet different school grounds qualities enhance girls’ and boys’ MCs in different ways.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".